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Record W4225130284 · doi:10.11159/iceptp22.203

Granitic Mining Waste Feasibility for Liner Material Production

2022· article· en· W4225130284 on OpenAlexvenueno aff
Leonardo Marchiori, António Albuquerque, Victor Cavaleiro

Bibliographic record

VenueProceedings of the World Congress on Civil, Structural, and Environmental Engineering · 2022
Typearticle
Languageen
FieldEngineering
TopicMining Techniques and Economics
Canadian institutionsnot available
FundersFundação para a Ciência e a Tecnologia
KeywordsProduction (economics)Environmental scienceWaste managementMining engineeringGeologyEngineering

Abstract

fetched live from OpenAlex

This work aims to characterize geotechnically and mechanically a granitic mine waste (MW), a clayey soil, and two mixtures of M:soil with 50% and 25% of (dry mass), looking to evaluate its feasibility for liner material production. Samples of MW, soil, M:soil(50:50%) M:soil(25:75%) were analysed in terms of specific gravity (GS), coarse and fine portions granulometry distributions, Atterberg limits (WL and WP), Normal Proctor compaction parameters (wopt and d,opt), oedometer compressibility test, consolidated undrained (CU) triaxial compression and hydraulic conductivity (k). MW showed finer granulometry, and higher plasticity than the soil, possibly showing filling properties for the mixtures, lower GS and d,opt indicating weight-reduction for a new liner material development. Furthermore, k values can reach the requirement for liner application of a minimum of 10 -9 m/s, although it needs more investigation on leachability capacity, cation exchange capacity and chemical compatibility in case addition of chemicals are needed for improving mixtures properties for liner material.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score0.686

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.009
GPT teacher head0.185
Teacher spread0.176 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations5
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of the World Congress on Civil, Structural, and Environmental EngineeringSame topicMining Techniques and EconomicsFrench-language works237,207